Increased understanding of global warming and climate change is driving current interest in the development of alternate renewable energy sources, including wind and solar energy. Presently, wind energy exploitation is the fastest-growing renewable energy industry (more than 30% per annum), accounting for 2% of world electrical energy production in 2010. Nevertheless, wind is intrinsically an unreliable energy source with relatively low conversion efficiency potential because it is largely unpredictable and there is a theoretical limit to the fraction of energy that can be extracted from it. These factors make wind a relatively expensive energy source and widespread adoption of wind energy systems is dependent on finding ways to minimize the costs associated with the materials, installation, and operation of those systems.
Minimizing the cost and maintaining the quality of electrical energy from wind power requires optimal energy extraction from wind at all times. This requires the accurate monitoring of both environmental and equipment conditions, and the use of real-time algorithms for optimization of power plant operation. An additional and crucial factor in the cost of wind power is its availability a defined as
  α  =      MTBF          MTBF      +      MTTR                      where MTBF is the mean time between failures, assumed constant, and MTTR is the mean time-to-repair (i.e., duration of the repair). The availability of many wind turbines in use today is around 98% owing to good reliability, maintenance management, and fast repairs. In spite of this, any reduction in the rate of equipment internal failures and any ways to minimize downtime for repairs are of critical importance for owners and operators of wind turbine systems. The wind turbine failures can be caused by external factors, such as lightning, fire, and earthquakes, but are most often caused by internal factors, stemming from the turbine equipment.        
Surveys of wind turbine internal failures indicate that the average risk of failure per year per turbine is around 40%. The highest failure rates and longest down-times are attributed to the gearbox, electric and control systems, the yaw system, and the generator, some repairs or replacements requiring more than 200 hours. These numbers are far too high for most wind turbine owners, especially for those that operate off-shore wind farms where the maintenance visits are particularly expensive and occur around once a year. The use of sensors of various types, including vibration and electrical sensors, to detect internal failures in real time is well established. However, the conventional response to the detection of internal failures is a complete shut down of the wind plant to prevent further damage. This inevitably incurs revenue loss. Waiting for the next scheduled maintenance visit to deal with the failure clearly prolongs the ongoing revenue loss, while immediate repairs would incur the additional expenditure of an unplanned visit. The increase in the cost of electricity from either the down-time or the increased expenses is highly undesirable, and there has been a substantial effort in the industry to implement fault-tolerant wind turbine designs and control algorithms to address these issues.
Fault tolerance is the ability to continue operation after a fault has occurred. A wind turbine equipped with fault-tolerant control system could continue operation, i.e., electricity generation, even after a fault has occurred, and the fault could be repaired at some later, more convenient time without decreasing availability of the generated electricity in the intervening period. Fault-tolerance increases MTBF and, hence, the availability of the wind plant.
Publicly available statistical data on wind turbine failures show that electromechanical failures in the generator provide a significant contribution to the overall wind turbine failure rate: as high as 20% per year per turbine. The most prevalent generator faults are bearing faults, stator or armature faults (short or open circuits), broken rotor bars and end ring faults in induction machines, and rotor eccentricity-related faults. Conventionally, these faults result in shutting down the wind turbine. Numerous approaches have been proposed and some implemented to reduce the MTBF resulting from above-mentioned faults. For example, MTBF can be improved by increasing the number of electrical phases in the generator or by adding redundancy in the electrical and mechanical systems. These approaches, redundancy in particular, most often come at the cost of increased complexity, mass and price, which is very disadvantageous in the already very cost-sensitive industry of energy generation. For these reasons, the industry is seeking more advanced solutions to fault tolerance, and would greatly benefit from the development of a fault-tolerant generator assembly at little or no added cost and complexity. This application discloses a system and a method for improving the availability of wind turbines electricity generation by implementing a method for operating a wind turbine generator in the presence of certain commonly encountered generator-fault conditions.